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3,709 results for “urbanization.”
FIGURE 3 in A new species of Phyllanthus (Phyllanthaceae) hiding in the shades in an urban Atlantic Forest in Rio de Janeiro State, Brazil
FIGURE 3. Geographic distribution of Phyllanthus celatus.
Humid Summers Promote Urban Aqueous-Phase Production of Oxygenated Organic Aerosol in the Northeastern United States
<p>Temporary private repository for peer review only. One file for Queens site and one file for Manhattan site measurements are included.</p>
Original survey data of conventional office workers and mobile workers in urban third places about flexible work behaviour
<p>3 simular surveys targeting conventional office workers and mobile workers in Guangzhou's Starbucks and Guangzhou Library. They examine workers' spatio-temporal behaviour and attitudes on flexible working.</p>
Essential Urban Land Cover Category Dataset - Samples
<p>This dataset, titled "Essential Urban Land Cover Category Dataset - Samples", contains sample data for five representative cities produced in the manuscript "Large-scale High-resolution Essential Urban Land Cover Category (EULCC) Mapping Using a Semantic-Augmented and Noise-Tolerant Approach". The raster data values range from 1 to 9, representing different essential urban land cover categories as follows:</p> <table> <tbody> <tr> <td>Values</td> <td>Classes</td> </tr> <tr> <td>1</td> <td>Building</td> </tr> <tr> <td>2</td> <td>Tree</td> </tr> <tr> <td>3</td> <td>Grass/Shrub</td> </tr> <tr> <td>4</td> <td>Parking lot</td> </tr> <tr> <td>5</td> <td>Road</td> </tr> <tr> <td>6</td> <td>Water</td> </tr> <tr> <td>7</td> <td>Barren</td> </tr> <tr> <td>8</td> <td>Agriculture</td> </tr> <tr> <td>9</td> <td>Others</td> </tr> </tbody> </table> <p> </p>
Energy Consumption Reduction in Historic Urban Residential Sectors: A Case Study of Kyoto City Using Bottom-Up Modeling and Future Climate Scenarios
<p>This dataset is a detailed simulation result of 21 scenarios in the paper. The results include:</p> <ol> <li>Annual daily energy consumption data divided by energy source and residential type.</li> <li>Photovoltaic power generation data, direct photovoltaic use, battery use, and photovoltaic power generation consumed by apartment houses and Kyomachiya through P2C systems. </li> <li>Annual daily net energy consumption data divided by energy source and residential type.</li> </ol>
A novel method to obtain three-dimensional urban surface temperature from ground-based thermography - Figure 10 median brightness temperatures
<p>Median brightness temperatures as shown in Figure 10 of Morrison et al. (2018) <em>A novel method to obtain three-dimensional urban surface temperature from ground-based thermography </em><a href="https://doi.org/10.1016/j.rse.2018.05.004">https://doi.org/10.1016/j.rse.2018.05.004</a></p> <p>Details on the files can be found below. Further details can be found in the linked paper and references. </p> <p><strong>Thermal infrared camera brightness temperature measurements</strong></p> <p><strong>02082014_COSMOTIRsunShade.csv:</strong><br> <strong>TIME</strong>: Local time. Timestep indicates end of 60 min aggregation interval using 1 min image samples.<br> <strong>class</strong>: sunlit (observed surface is in direct sun) or shaded (observed surface is in shade)<br> <strong>median_Tb_K</strong>: median brightness temperature across all images and image pixels for the given class and timestep (K)</p> <p><strong>02082014_COSMOTIRorientations.csv:</strong><br> <strong>TIME</strong>: Local time. Timestep indicates end of 60 min aggregation interval using 1 min image samples.<br> <strong>class</strong>: sunlit (observed surface is in direct sun) or shaded (observed surface is in shade) also stratified by surface orientation i.e. <sun_status>_<orientation><br> <strong>median_Tb_K</strong>: median brightness temperature across all images and image pixels for the given class and timestep (K) </p> <p><strong>002082014_COSMOTIRorientationsAndSunShade.csv:</strong><br> <strong>TIME</strong>: Local time. Timestep indicates end of 60 min aggregation interval using 1 min image samples.<br> <strong>class</strong>: sunlit (observed surface is in direct sun) or shaded (observed surface is in shade) also stratified by surface orientation i.e. <sun_status>_<orientation><br> <strong>median_Tb_K</strong>: median brightness temperature across all images and image pixels for the given class and timestep (K) </p> <p> </p> <p><strong>Supplementary standard meteorological and radiation measurements.</strong></p> <p><strong>MET_RAD_Morrisonetal_2018.csv</strong>:</p> <p><strong>TIME</strong>: Local time. 10 min end of average of 1 min samples.<br> <strong>press</strong>: Atmospheric pressure (hPa) (site: JMA Kumagaya AMeDAS)<br> <strong>Tair</strong>: Air temperature (degrees celsius) (site: JMA Kumagaya AMeDAS)<br> <strong>RH</strong>: Relative humidity (%) (site: JMA Kumagaya AMeDAS)<br> <strong>WS</strong>: Wind speed (m/s) (site: JMA Kumagaya AMeDAS)<br> <strong>SWdn_direct</strong>: Direct incoming shortwave radiation (W m-2) (site: COSMO, Eko MS-56)<br> <strong>SWdn</strong>: Hemispherical incoming shortwave radiation (W m-2) (site: COSMO, Eko MR-40)<br> <strong>SWup</strong>: Hemispherical outgoing shortwave radiation (W m-2) (site: COSMO, Eko MR-40)<br> <strong>LWdn</strong>: Hemispherical incoming longwave radiation (W m-2) (site: COSMO, Eko MR-40)<br> <strong>LWup</strong>: Hemispherical outgoing longwave radiation (W m-2) (site: COSMO, Eko MR-40)</p> <p> </p>
Figure 2 in Urban heronry birds tolerate human presence more than its conspecific rural birds
Figure 2. Flight initiation distances of four species of heronry in urban and rural habitats.
Urban-PLUMBER: Flux tower data archive – MX-Escandon
<p>Eddy covariance flux tower dataset from Escandon, Mexico City (Jun. 2011 – Sep. 2012) for the URBAN-PLUMBER model evaluation project (<a href="https://urban-plumber.github.io/MX-Escandon/">https://urban-plumber.github.io/MX-Escandon/</a>). Urban-PLUMBER evaluates the performance of land surface models used in meteorological or climatic simulations of urban areas (<a href="https://urban-plumber.github.io/">https://urban-plumber.github.io/</a>).</p>
Urban-PLUMBER: Flux tower data archive – SG-TelokKurau
<p>Eddy covariance flux tower dataset from Telok Kurau, Singapore (March 2015 – Feb. 2016) for the URBAN-PLUMBER model evaluation project (<a href="https://urban-plumber.github.io/SG-TelokKurau/">https://urban-plumber.github.io/SG-TelokKurau/</a>). Urban-PLUMBER evaluates the performance of land surface models used in meteorological or climatic simulations of urban areas (<a href="https://urban-plumber.github.io/">https://urban-plumber.github.io/</a>).</p>
Urban-PLUMBER: Flux tower data archive – PL-Narutowicza
<p><br> # Urban-PLUMBER site data collection</p> <p>Files in this folder are associated with the manuscript:</p> <p>> "Harmonized, gap-filled dataset from 20 urban flux tower sites"</p> <p>Use of any data must give credit through citation of the above manuscript and other sources as appropriate.<br> We recommend data users consult with site contributing authors and/or the coordination team in the project planning stage. <br> Relevant contacts are included in timeseries metadata.</p> <p>For site information and timeseries plots see https://urban-plumber.github.io/sites.</p> <p>For processing code see https://github.com/matlipson/urban-plumber_pipeline.</p> <p>### Included files</p> <p>Within each site folder:</p> <p>- `index.html`: A summary page with site characteristics and timeseries plots.<br> - `SITENAME_sitedata_vX.csv`: comma seperated file for numerical site characteristics e.g. location, surface cover fraction etc.<br> - `timeseries/` (following files available as netCDF and txt)<br> - `SITENAME_raw_observations_vX`: site observed timeseries before project-wide quality control.<br> - `SITENAME_clean_observations_vX`: site observed timeseries after project-wide quality control. <br> - `SITENAME_metforcing_vX`: site observed timeseries after project-wide quality control and gap filling.<br> - `SITENAME_era5_corrected_vX`: site ERA5 surface data (1990-2020) with bias corrections as applied in the final dataset.<br> - `log_processing_SITENAME_vX.txt`: a log of the print statements through running the create_dataset_SITENAME scripts.</p> <p>### Authors</p> <p>Mathew Lipson, Sue Grimmond, Martin Best, Andreas Christen, Andrew Coutts, Ben Crawford, Bert Heusinkveld, <br> Erik Velasco, Helen Claire Ward, Hirofumi Sugawara, Je-Woo Hong, Jinkyu Hong, Jonathan Evans, Joseph McFadden, <br> Keunmin Lee, Krzysztof Fortuniak, Leena Järvi, Matthias Roth, Nektarios Chrysoulakis, Nigel Tapper, Oliver Michels, <br> Simone Kotthaus, Stevan Earl, Sungsoo Jo, Valéry Masson, Winston Chow, Wlodzimierz Pawlak, Yeon-Hee Kim.</p> <p>Corresponding author: Mathew Lipson <m.lipson@unsw.edu.au></p>
Urban-PLUMBER: Flux tower data archive – PL-Lipowa
<p># Urban-PLUMBER site data collection</p> <p>Files in this folder are associated with the manuscript:</p> <p>> "Harmonized, gap-filled dataset from 20 urban flux tower sites"</p> <p>Use of any data must give credit through citation of the above manuscript and other sources as appropriate.<br> We recommend data users consult with site contributing authors and/or the coordination team in the project planning stage. <br> Relevant contacts are included in timeseries metadata.</p> <p>For site information and timeseries plots see https://urban-plumber.github.io/sites.</p> <p>For processing code see https://github.com/matlipson/urban-plumber_pipeline.</p> <p>### Included files</p> <p>Within each site folder:</p> <p>- `index.html`: A summary page with site characteristics and timeseries plots.<br> - `SITENAME_sitedata_vX.csv`: comma seperated file for numerical site characteristics e.g. location, surface cover fraction etc.<br> - `timeseries/` (following files available as netCDF and txt)<br> - `SITENAME_raw_observations_vX`: site observed timeseries before project-wide quality control.<br> - `SITENAME_clean_observations_vX`: site observed timeseries after project-wide quality control. <br> - `SITENAME_metforcing_vX`: site observed timeseries after project-wide quality control and gap filling.<br> - `SITENAME_era5_corrected_vX`: site ERA5 surface data (1990-2020) with bias corrections as applied in the final dataset.<br> - `log_processing_SITENAME_vX.txt`: a log of the print statements through running the create_dataset_SITENAME scripts.</p> <p>### Authors</p> <p>Mathew Lipson, Sue Grimmond, Martin Best, Andreas Christen, Andrew Coutts, Ben Crawford, Bert Heusinkveld, <br> Erik Velasco, Helen Claire Ward, Hirofumi Sugawara, Je-Woo Hong, Jinkyu Hong, Jonathan Evans, Joseph McFadden, <br> Keunmin Lee, Krzysztof Fortuniak, Leena Järvi, Matthias Roth, Nektarios Chrysoulakis, Nigel Tapper, Oliver Michels, <br> Simone Kotthaus, Stevan Earl, Sungsoo Jo, Valéry Masson, Winston Chow, Wlodzimierz Pawlak, Yeon-Hee Kim.</p> <p>Corresponding author: Mathew Lipson <m.lipson@unsw.edu.au></p>
Modelizations and analyzes of the urban fabric (2D and 3D) of Charleville from 1724 to 1876.
<p>The main characteristic of the city of Charleville (Ardennes), concerning the history of its population, is the realization by the municipal authorities of a nominative, spatial and annual census of the inhabitants, undertaken from the end of the 17th century, and until at the beginning of the 20th century.<br> This gives the possibility of exploiting Carolopolitan data within a geographic information system (GIS). Thanks to this GIS, to its informal quality and volume, it is possible to reconstruct in 3D the city of 1834, and to make full use of the methodological environment known as "BIM" (or Building Information Model). BIM will make it possible to exploit the architectural and demographic composition of each plot, block, dwelling in this city, from its genesis to the present day, like a real 3D GIS.<br> Spatial analyzes built from cartographic and topographic data, analyzed, vectorized (2D and 3D), georeferenced and linked to the occupation data of the city of Charleville.<br> <br> Data collected, digitized and structured from 01/15/2016 to 01/04/2021 in the context of:<br> - Axis 1 of the Roland Mousnier Center (UMR 8596), Sorbonne University / CNRS<br> - the C2EP2 Project funded by the Sorbonne University "Emergencies" call for projects (2019-21) for the web and BIM parts (CSTB partnership)<br> - scientific and technical collaboration (partnership agreement) between the National Archives and the Roland Mousnier Center.<br> <br> Creative Commons License<br> Dataset "Analyzes of the urban fabric (2D and 3D) of Charleville from 1724 to 1876.". by Sylvain Rassat, Roland Mousnier Center, CNRS, Departmental Archives, National Archives is made available under the terms of the Creative Commons Attribution - Share under the Same Conditions 4.0 International license.<br> Based on a Source Link work.<br> Permissions beyond the scope of this license can be obtained at https://www.researchgate.net/profile/Sylvain_Rassat.<br> (https://cesium.cstb.fr/Apps/cnrs/MN_Charleville3D.html)</p>
The development and validation of an Inhomogeneous Wind Scheme for Urban Street
<p>This datasets include the following three parts:</p> <ol> <li>the resulting data in paper shown in the Resulting_datasets.zip</li> <li>the source code for IWSUS_v0.1 and the test case are in https://doi.org/10.5281/zenodo.7488104.</li> <li>the CFD simulation for perpendicualr and parallel scenerios at https://doi.org/10.5281/zenodo.7371305 and https://doi.org/10.5281/zenodo.7371804 respectively.</li> <li>The coupling codes for IWSUS-v0.1 with Weather Research and Forecasting model (WRFV3.9.1.1) and Gotherburg cascan be downloaded in https://github.com/krmyArag/IWSUS.</li> </ol> <p>In supplement. docx more CFD simulation results used to develop the IWSUS scheme are included, which cannot be fully presented in the paper due to the limitation of the length of the article.</p>
A multiplicity of perspectives on complex urban water systems transformation - a systematic review (supplemental data)
<p>This supplemental data contains all records (publication and reference materials) used in the systematic review of the literature (publication pending):</p> <p>1) Full list of publication records on urban water literature using the social-ecological systems and socio-technical systems framework extracted from the Web of Science and Scopus database (raw list).</p> <p>2) Selected list of corpus and sub-corpus literature from the original list after applying the inclusion and exclusion criteria.</p> <p>3) Keywords mapping drawn from the reference list using the Vosviewer application.</p>
Dataset - Mapping the key drivers of mega-urbanisation in contemporary urban development
<p>This dataset includes multiple scales and a long-term perspective in three distinct socio-economic settings, i.e. Germany, Japan and China’s Yangtze River Delta region and visualisations of results on urban development trends over 45 years.</p>
Emeprical Studies on the difference between urban and rural of different areas in China
Open the record for dataset details and reuse information.
Gene expression profiling of juvenile salmon in Pacific Northwest urban streams
GEO Series GSE115688. Oncorhynchus kisutch. 57 samples. Type: Expression profiling by array.
Input data for a spatial urban sprawl model
<p>Input data for projecting global urban extent under future shared socioeconomic pathways (2010-2100)</p>
Case Study - Office and Residential - Geneva Urban
<p>This data set should contain several distinct types of files for a case study based in Geneva. The files are either inputs (IDF), or outputs (CSV, EIO, etc.). The weather files are in a related data entry (TO BE LINKED). The files have mostly been zipped based on dates. </p> <p>The buildings model correspond to real plots in Geneva, but the simulations are not meant to represent the actual buildings that stand there. The models are based on estimated constructions from the era of the building. While the heating load of the buildings should fall within the same order of magnitude as recorded values for Geneva, it will not match the bills of the real building that stands on a particular site.</p> <p>The weather file name is included in the name of the output. Consult the weather file dataset (TO BE LINKED) for an explanation of the naming scheme. </p>
Speedy urbanization ratios
<p>TEST</p> <p>Urabization ratios calculated for sampling sites. Calculated for buffers with increasing radii and based upon GRB dataset from Grootschalig Referentie Bestand (AGIV).</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.